Concepts are basic elements of natural language processing, studying on concept representation and transformation between connotation and extension become more and more important. Multi-granularity concept extraction is still a difficult problem in uncertainty knowledge representation. Cloud model is an uncertainty cognition model, which realizes the bidirectional transformation between a qualitative concept and quantitative data by Gaussian cloud algorithm. Gaussian cloud transformation provides a method to transform a group of data in problem domain to multiple concepts in different granularities in cognition domain. This paper introduces cloud model and Gaussian cloud transformation algorithm to describe the multi-granularity concepts. A case study is also given to prove the effectiveness of the proposed method.